Foreign Language Teacher Training in the Sudan: Past, Present and Strategies for Future Recruitment Policies
Bibliographic record
Abstract
The qualifying of teachers secures the attainment of the national educational objectives, but to achieve these goals, strict criteria about teacher quality must be utilized. However, it is quite clear that whatever measures are to be adopted to deal with these educational issues, it is always the teachers who will have to put these objectvies into reality.This paper is suggesting some ideas to improve the teaching profession. The recent recruitment policy of teachers in the country attracts only the poor achievers, who are unwilling to teach but they aspire to just get a degree. This paper suggests abolishing all colleges of education and encouraging the future teacher to join a one-year training course after s/he has got his/her BA or B.Sc. This policy will attract the willing persons who are serious to take teaching as their profession. Then the candidates can spend this one academic year to be equipped with necessary pedagogical knowledge to qualify to manage his/her classroom efficiently and carry out effective classroom presentation. By this recruitment policy, we can guarantee the sustainability of the process, and that only the willing persons will come to take teaching as their future career.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".